Large Language Models for Native Garden Design and Visualization

Presenter

Kabeera Singh

Campus

UMass Amherst

Sponsor

Daniel Buonaiuto, Department of Environmental Conservation, UMass Amherst

Schedule

Session 1, 10:30 AM - 11:15 AM [Schedule by Time][Poster Grid for Time/Location]

Location

Poster Board A30, Campus Center Auditorium, Row 2 (A21-A40) [Poster Location Map]

Abstract

The overuse of traditional lawns in suburban areas poses a significant environmental challenge, characterized by high resource consumption, chemical inputs, and diminished biodiversity. In response, this project develops a user-friendly web application to assist homeowners in transitioning their lawns into biodiverse native gardens. By leveraging Python and OpenAI's API to use Large Language Models like ChatGPT, this application provides personalized recommendations based on local environmental conditions and user preferences, encompassing a comprehensive database of native plants, hardiness zones, and local nurseries. Through intuitive design, this project aims to streamline sustainable landscaping practices, making them accessible to a broader audience. Informed by feedback from the Spatial Ecology Lab at UMass and the ICONS program, this project emphasizes usability, functionality, and ecological importance, ultimately empowering homeowners to play a proactive role in fostering diverse and self-sustaining ecosystems within their communities.

Keywords

Large Language Models, Ecology, Sustainability, Web Application, Environment

Research Area

Environmental Science and Sustainability

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